This work proves a formal impossibility theorem stating that no observable behavioral or biometric signal can serve as a cryptographic secret under standard semantic security notions (IND-CPA / IND-CCA), in any computational model admitting machine learning approximation and side-channel observability. The result holds in classical, post-quantum, and hybrid adversarial models. We further derive strict architectural consequences for biometric authentication, fuzzy extractors, and behavioral identification systems, showing that such signals may only function as zero-knowledge liveness proofs, not as entropy sources for cryptographic key material.
Secure Multi-party Computation (MPC) considers the problem where a set of mutually distrusting parties want to jointly compute a function over their private inputs, without revealing any extra information about these inputs other than what it can be inferred from the output of the function. This setting is well-motivated, and it has many real-world applications such as auction, voting, etc. MPC can be also seen as a generalization of many natural cryptographic primitives. For example, zero-knowledge (ZK) can be viewed as a special case of two-party secure computation. In ZK, a party, called prover aims to convince a second party, called verifier, that the prover’s private input witness w and a public input statement x belong to a relation R. An important research direction in secure computation is to find the trade-off between the required setup (e.g., the use of the broadcast channel, the use of common reference string (CRS) / public key infrastructure (PKI), the upper bound of the parties that can be corrupted, etc.), and the security guarantees that can be achieved. The setups can be viewed as some general assumptions that the protocol needs to satisfy, and they influence the usability of the protocol in real-world scenarios. In principle, having simpler (or no) setups mean that the protocol is more general and can be more useful in real-world scenarios. At the same time, having simpler setups may lead to weaker security guarantees. Therefore, finding the trade-off between setup and security guarantees is important and meaningful. In this thesis, we target MPC and ZK, and we focus on how to minimize the setup for MPC and ZK while still providing meaningful levels of security. More specifically: Regarding MPC, we focus on the dishonest majority (i.e., the adversary can corrupt all but one party), and we aim at 1) minimizing the use of broadcast channels. 2) studying the MPC with pre-processing when no setup is available. • Informally, a broadcast channel guarantees that when a message is sent, this reaches all the parties, without ambiguity. It also guarantees that if an honest party receives a message from a corrupted party, then it is guaranteed that all the honest parties have received the message. To realize broadcast, parties in the protocol could run the broadcast protocol, which may require many rounds of peer-to-peer communications. An alternative way is to rely on physical or external infrastructure such as blockchain. In both cases, broadcast is expensive, as such, we want to minimize its use. In particular, this thesis presents the following results: – When assuming no setup, we give a complete characterization with respect to the use of broadcast channels, and we obtain the optimal results. – We consider the same problem for the case that we only want to allow the black-box use (i.e., do not have access to the code of the algorithm) of the oblivious transfer protocol. We also give a characterization. • In the standard definition of MPC, the parties’ private inputs are fixed before the start of the protocol. However, there is another type of MPC named MPC with pre-processing, where the protocol can pre-compute some messages without using parties’ inputs, and these messages can accelerate computations in the online phase (i.e., other computations that require parties’ inputs). Since some expensive computations can be pre-computed, the online phase could be more lightweight. Therefore, we want to remove the dependency of the input from as many rounds as possible, so that we can do some pre-processing. In this direction, we explore the protocol with no setup. We provide a compiler that can turn a big class of MPC protocol that may require the inputs already to compute the first round, into a new protocol that needs the inputs only in the last two rounds. We also propose new MPC definitions that capture this delayed-input features. Regarding ZK, we do the following: • In standard single-theorem ZK definition, the security of the ZK protocol is guaranteed to hold only when one proof is issued. In the case where multiple zero-knowledge proofs need to be issued (i.e., to prove multiple NP statements), each new zero-knowledge proof requires a freshly generated setup. In the multi-theorem ZK definition, instead, one setup is sufficient for generating multiple zero-knowledge proofs for multiple instances. We propose a multi-theorem protocol (in the format of a compiler) that follows the Fiat-Shamir paradigm and relies on correlation intractable hash functions. Moreover, our protocol remains zero-knowledge and sound even against adversaries that choose the statement to be proven (and the witness for the case of zero-knowledge) adaptively on the key of the hash function. Prior works could achieve this adaptive security only inefficiently via NP reductions. • ZK protocols are secure only when all setups are correctly generated, but in real-world scenarios, some of the setups may not be correctly generated. For instance, to run a non-interactive zero-knowledge (NIZK) protocol, the setup CRS could be chosen with bias. In this case, the security of the NIZK protocol does not hold anymore. Instead of finding a secure ZK candidate, one alternative solution is to have multiple instantiations of ZK candidates and assume that only for a subset of them the setup is generated correctly. More formally, we consider the case where only a subset of the instances are secure. In more detail, given access to n candidate instantiations of a NIZK for some language, we want to have a construction that itself implements a NIZK for the same language without relying on any additional computational assumptions. We refer to this type of construction as combiner, and the combiner is secure assuming at least t of the given candidates are secure. In this work, we provide three different constructions of robust NIZK combiners and show that combiners are impossible to realize unless the majority of the input candidates are secure.
Abstract This research presents the Aegis Framework, a groundbreaking secure and upgradeable digital token contract system that fundamentally addresses cryptocurrency scam prevention through innovative smart contract architecture. The framework implements a novel timelock-protected proxy pattern that eliminates instant rug pull vulnerabilities while maintaining essential upgrade capabilities. Developed through systematic implementation of advanced smart contract patterns, the Aegis Framework comprises three core components: AegisToken (a secure, pausable ERC20 token with role-based access control), AegisProxy (an upgradeable proxy system using UUPS pattern), and AegisTimelock (a revolutionary mandatory delay mechanism for all upgrades). Technical validation confirms successful compilation of all contracts with AegisToken (2782 bytes, 17 functions), AegisProxy (1771 bytes, 8 functions), and AegisTimelock (680KB comprehensive security contract). The framework's security architecture prevents single-point-of-failure risks by separating roles (Owner, Minter, Pauser, Upgrader) and enforcing minimum delay periods (configurable from 1–7 days) for all contract upgrades. Implementation results demonstrate complete prevention of instant malicious upgrades, transparent upgrade processes with community notification periods, and emergency response capabilities through instant pausable mechanisms. Compared to existing solutions, the Aegis Framework introduces the first integrated timelock security system specifically designed for token contracts, addressing critical gaps identified in recent smart contract security literature. The complete system includes Python-based deployment tools, comprehensive validation scripts, and production-ready compiled contracts, establishing a new standard for secure token implementations in decentralized finance applications.
Contemporary Online Social Networks (OSNs) present critical vulnerabilities in user authentication and data integrity protocols. Since the social network is a multi-user platform, it requires a well-performing authentication mechanism that works along with the blockchain to ensure secure transactions. The existing methodologies exhibit significant limitations, particularly susceptibility to quantum cryptanalysis and privacy vector compromises. This study proposes a novel blockchain-based framework for decentralized OSNs, implementing smart contracts and InterPlanetary File System (IPFS) protocols to establish a distributed authentication architecture that mitigates these vulnerabilities while maintaining computational efficiency. Initially, we propose a post-quantum digital signature followed by a blockchain system using the signatures. Unlike previous OSNs, our solution uses post-quantum approaches, making it secure against both classical and quantum attacks. To enhance the data authentication of social network users, this research leverages the post-quantum multimodal biometric-based approach, where an improved version of Crystals Dilithium 3 is utilized in place of ECDSA in the XRP Ledger (XRPL) blockchain. We have integrated different post-quantum algorithms with XRPL using the open quantum safe library (liboqs) and compared the results in terms of resource consumption. The research explores the advantages of the proposed approach, highlighting its potential to mitigate the shortcomings of conventional methods and ensure secure data transmission in the era of quantum computing.
This article examines the evolutionary trajectory of contactless payment systems across closed-loop and open-loop architectures, tracing their development from magnetic stripe foundations through EMV chip technology to contemporary NFC implementations with cryptogram-based security. The comparative analysis highlights how closed-loop systems deliver enhanced customer loyalty and data ownership, while open-loop networks provide global accessibility and financial inclusion. The security architecture of contactless payments is explored through a detailed examination of cryptogram-based authentication, tokenization mechanisms, vulnerability mitigation strategies, and biometric integration. Future directions reveal emerging trends, including digital-only credential issuance, integration with adjacent technologies such as IoT and distributed ledgers, evolving consumer trust dynamics, and the developing regulatory landscape. The article illuminates how contactless innovation continues to reshape retail finance while balancing convenience, security, and commercial objectives across payment environments by analyzing these technological and ecosystem factors.
Abstract In today’s era of digital transformation, online transactions have become vital to financial systems, e-commerce, and decentralized applications. However, increasing dependence on digital payment infrastructures has also raised major security concerns such as hacking, identity theft, and unauthorized access. To address these challenges, the proposed project “Blockchain Secure Transaction” presents a decentralized framework that ensures transparency, integrity, and confidentiality in digital transactions. The system uses blockchain technology to record and validate each transaction in a distributed ledger, eliminating centralized control and making data immutable and tamper-proof. The workflow begins with user registration, where users provide details and set a picture password for secure recognition. During login, the system verifies credentials and performs biometric authentication to confirm user identity. Unregistered users are redirected to the registration page, maintaining process integrity. Once authenticated, users access the dashboard to initiate secure transactions. To preserve privacy, Zero-Knowledge Proof (ZKP) is used, allowing users to prove transaction authenticity without revealing sensitive information. Transactions then pass through smart contract verification, which ensures compliance with predefined conditions. Successful verifications result in completed transactions, while suspicious or invalid ones are blocked or frozen automatically. All user data and transaction logs are securely stored in Firebase, with backend processing handled in Java and the frontend designed using React (app.jsx). By combining blockchain’s immutability, smart contract automation, ZKP privacy proofs, and biometric authentication, the Blockchain Secure Transaction System offers a multi-layered, tamper-resistant, and transparent solution for secure online payments — enhancing trust and reliability in the digital economy.
Kassem Danach, Abbas Tarhini, Wael Hosny Fouad Aly, Hussin Hejase
Blockchain technology relies on cryptographic mechanisms for transaction security and data integrity. However, the growing computational complexity, high transaction costs, and scalability issues pose significant challenges to blockchain adoption. Traditional cryptographic methods—such as hashing, key generation, encryption, and decryption—introduce excessive computational overhead, leading to energy inefficiencies and increased latency. This research proposes an optimization-driven crypto analysis framework that integrates metaheuristic algorithms, combinatorial optimization, reinforcement learning, and game theory to enhance the efficiency and security of blockchain cryptographic processes. The framework focuses on optimized cryptographic computation, gas fee reduction in smart contracts, security enhancement against cryptanalysis, and improved scalability of consensus mechanisms. Experimental evaluations demonstrate up to 39.4\% reduction in cryptographic execution time, 29.4\% savings in smart contract gas fees, and 33.3\% improvement in decentralization of Proof-of-Stake validators. These results validate the effectiveness of the proposed framework in achieving secure, scalable, and cost-efficient blockchain operations.
Blockchain technology has emerged as a transformative solution for decentralized and secure data management. However, the security of blockchain networks heavily relies on robust cryptographic protocols. This article provides a comprehensive analysis of key cryptographic techniques employed in blockchain security, including hash functions, digital signatures, consensus algorithms, and zero-knowledge proofs. We evaluate their roles in ensuring data integrity, authentication, confidentiality, and resistance to common attacks such as double-spending and Sybil attacks. A comparative study highlights the strengths and limitations of these protocols, guiding future enhancements for blockchain security frameworks
Decentralized authentication in dynamic mobile networks faces significant challenges due to high node mobility, resource constraints, and vulnerabilities to side-channel attacks. In this work, we present MobiAuth , a blockchain-driven framework based on Hyperledger Iroha and OMNET ++ that enables secure, peer-to-peer authentication using compact Ed25519 signatures and ephemeral session keys. Our protocol eliminates single points of failure by distributing trust across a permissioned ledger and employs constant-time cryptographic operations to thwart timing and power-analysis attacks. We validate MobiAuth through co-simulation in OMNET ++ integrated with Iroha via a Python gRPC bridge and benchmark its performance with Hyperledger Caliper. Simulation yields 95% packet delivery with an authentication latency ranging from 12 ms in the only OMNeT ++ and baseline to 20–150ms in the full ledger-integrated system, and a ledger write throughput of 250tps. Comparative experiments demonstrate a 33% reduction in communication overhead and robust operation under random Control Point failures and Byzantine Access Node behavior. Analysis of on-device ledger synchronization further highlights practical storage growth and bandwidth requirements for long-term deployment. These results indicate that MobiAuth achieves strong security and privacy with modest energy impact, scalable performance, and compatibility with mobile devices in real-world network environments. • Vulnerabilities of mobile network devices in a dynamic environment. • Blockchain-based automatic authentication for mobile devices. • Enhanced security and privacy with Ed25519 curve cryptography. • OMNET++ simulation on Hyperledger Iroha for mobile network. • Protocol verification using Scyther for testing security protocol strength.
Driven by the increasing demand for multi-party data computation, Private Set Intersection (PSI) has become a pivotal technique for secure data sharing and privacy preservation. Although several efficient two-party PSI protocols have been developed, multi-party scenarios continue to suffer from limited computational efficiency and inadequate security guarantees. To address this engineering challenge, this study aims to enhance the performance and security of multi-party PSI protocols. We introduce SM-MPSI, a multi-party PSI protocol built upon national cryptographic standards. This protocol integrates SM2 and SM3 cryptographic mechanisms, employs non-interactive zero-knowledge proofs for identity authentication, and leverages domestic secure cryptographic chips to accelerate core algorithms. Experimental comparisons with existing mainstream protocols demonstrate significant improvements in computational efficiency and system scalability, while preserving robust security guarantees. Furthermore, SM-MPSI achieves enhanced communication efficiency and reduced resource consumption in multi-party scenarios. This research offers technical contributions toward advancing China's efforts in independent innovation in privacy-preserving computing and cryptographic technologies, thereby laying a solid foundation for strengthening national cybersecurity capabilities.
Digital transactions currently exceed trillions of dollars annually, yet traditional paper-based agreements remain a bottleneck for automation, enforceability, and dispute resolution. Natural language contracts introduce ambiguity, require manual processing, and lack computational verifiability, all of which hinder efficient digital commerce. Computable legal contracts, expressed in machine-readable formats, offer a potential solution by enabling automated execution and verification. Blockchain-based smart contracts further strengthen enforceability and accelerate dispute resolution; however, current implementations risk exposing sensitive agreement terms on public ledgers, raising serious privacy and competitive intelligence concerns that limit enterprise adoption. We introduce zk-agreements, a protocol designed to transition from paper-based trust to cryptographic trust while preserving confidentiality. Our design combines zero-knowledge proofs to protect private agreement terms, secure two-party computation to enable private compliance evaluation, and smart contracts to guarantee automated enforcement. Together, these components achieve both privacy preservation and computational enforceability, resolving the fundamental tension between transparency and confidentiality in blockchain-based agreements.
This paper addresses the challenge of designing secure and private digital credentialing systems by leveraging advanced mathematical primitives from applied cryptography. The core of our proposed solution is the application of Zero-Knowledge Proofs (ZKPs), a class of cryptographic protocols that allows for the verification of assertions without disclosing the underlying secret data. We introduce a formal, layered architecture that demonstrates how the mathematical properties of ZKPs can be systematically translated into a robust, large-scale information system. The framework's design is validated against the complex requirements of the academic domain, which serves as a rigorous testbed for our architectural approach. The primary contribution is a blueprint for integrating complex cryptographic protocols into practical system design, demonstrating how mathematical guarantees of privacy can be preserved in a distributed and verifiable manner. This work provides a novel contribution at the intersection of applied cryptography, system architecture, and information security.
W. M. A. B. Wijesundara, Joong-Sun Lee, Eleni Aloupogianni, Dara Tith · 6 authors
Rapid proliferation of smart home IoT devices has intensified the demand for secure, scalable, and autonomous firmware authentication mechanisms. Traditional centralized solutions face challenges related to privacy concerns, limited scalability, and vulnerability to single point of failure. In this paper, we propose DIDAuth-IoTFW, a novel decentralized identity and firmware authentication framework that uniquely integrates Ethereum Layer-2 Arbitrum, InterPlanetary File System (IPFS), and W3C-compliant Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs). DIDAuth-IoTFW provides a complete firmware authentication life cycle, from decentralized identity registration to real-time, on-chain verifiable revocation. While enabling autonomous, cryptographic verification directly on resource-constrained IoT devices and ensuring reliable performance even when gateways are compromised or unavailable. Our proof-of-concept implementation on ESP32 and Raspberry Pi achieved complete resistance to replay, forgery, and revocation threats with verification consistently under 1.2 s. Compared to prior work, DIDAuth-IoTFW uniquely combines firmware–VC hash binding, contract binding that prevents cross-registry replay, and device-side enforcement resilient to gateway compromise. Experimental results indicate a robust, privacy-preserving, and scalable alternative to centralized firmware-update pipelines for smart-home IoT.
The rapid adoption of Internet of Things (IoT) in Healthcare has significantly enhanced real-time patient monitoring and decision making. However, security and privacy still remain the major concern due to sensitive medical data of patients especially on low-power IoT devices. Traditional authentication schemes like Zero Knowledge Proof (ZKP) and Elliptic Curve Cryptography (ECC) often struggle with efficiency in resource-constraint environments due to their computational overhead. In order to address these challenges, we propose a Neural-Based Hybrid and Adaptive Framework that combines Schnorr ZKP with Kyber-based key encapsulation, using a neural network to dynamically select Kyber variants (512, 768, 1024) based on device parameters (type, authentication time, transmission time) to balance security and efficiency for low-power IoT devices. Extensive experiments validated robust security against replay and spoofing attacks, achieving authentication success for legitimate clients and zero attack successes. Furthermore, our proposed framework outperforms traditional Kyber1024 and ZKP/ECC based authentication schemes in terms of authentication time and computational overhead making it robust and scalable solution for sensitive and resource-limited environments like HealthCare IoT systems. • Design a novel hybrid authentication framework that integrates ZKP and Kyber PQC (Post Quantum Cryptography) to ensure secure and efficient authentication for IoT healthcare devices. • Utilize Neural Network to intelligently select the most appropriate Kyber variant based on threat level and computational efficiency. • Provide comprehensive experimental analysis comparing the proposed hybrid and adaptive framework with traditional ZKP, ECC and static Kyber implementations.
Traceable Ring Signatures (TRS) were introduced by Fujisaki and Suzuki~[PKC'07], where a trace algorithm can publicly check if two signatures with the same event label were generated by the same signer (linkability). In addition, if the two signatures correspond to different messages, then the signer's identity is revealed (traceability). Following [PKC'07], most subsequent works adopt the same definitions and consider three security properties, anonymity, linkability, and exculpability. [PKC'07] proved that the latter two properties together imply unforgeability, a fundamental requirement for all signature-like primitives. ~~~~In this work, we identify a gap in the aforementioned proof, which arises from the insufficient consideration of linkability and exculpability in [PKC'07]. To address this, we revisit the syntax and security notions of TRS, and close this gap by defining extended linkability and extended exculpability. Building on these, we design a new framework of TRS from PseudoRandom Functions (PRF) and Zero-Knowledge Proofs of Knowledge (ZKPoK) that supports tracing, provided that both two signatures are valid. This constitutes a substantial improvement over existing approaches---all of which require tracing with the size of the ring---and elevates TRS to a level of practicality and efficiency comparable to Linkable Ring Signatures (LRS), which have already achieved widespread deployment in practice. Finally, we instantiate our generic framework from the DDH assumption and leverage the Bulletproofs [S\&P'18] to construct a TRS scheme with log-size signatures. The proposed scheme achieves highly optimized signature sizes in practice and remains compatible with most existing DLog-based systems. On Curve25519, the signature size is bytes, which to our best knowledge is the shortest LRS scheme for a ring .
The article presents a comprehensive overview of zero-knowledge proof (ZKP) protocols as a fundamental concept of modern cryptography. The historical background of their emergence and the main properties ensuring reliability and confidentiality, i.e., completeness, soundness, and zero-knowledge — are considered. A classification of protocols into interactive and non-interactive ones is provided, with a special focus on modern solutions such as the zk-SNARK and the zk-STARK. The mathematical foundations of ZKPs are described in detail, including discrete logarithm proofs, the use of homomorphic encryption, polynomial commitments, hashing, and elliptic curves. Practical application areas are analyzed, including cryptocurrencies (Zcash, Ethereum), authentication systems, digital identity, and electronic voting. The advantages of using ZKPs are shown, such as enhanced privacy, reduced need for trusted intermediaries, and strengthened security. At the same time, key challenges are outlined, including scalability, implementation complexity, the problem of trusted setup, and potential vulnerability to quantum computing. It is concluded that zero-knowledge proof protocols are a powerful tool for ensuring confidentiality and reliability of digital systems, while further research is aimed at creating more efficient and quantum-resistant solutions.
Designing secure electronic voting systems that truly protect voter privacy, ensure vote accuracy, and allow independent verification continues to pose serious difficulties. Many current cryptographic approaches require excessive computational resources and use encryption keys that are too large for practical implementation. This paper proposes modifications to the Chaum, Pedersen and Cramer, Franklin, Schoenmakers, and Yung voting protocols by integrating elliptic curve cryptography (ECC), which offers stronger security per bit and more compact key representations. The use of ECC allows for reduced parameter sizes while maintaining resistance against known attacks, including those targeting the discrete logarithm problem. We present detailed adaptations of these protocols on elliptic curves and demonstrate how they preserve core security properties such as vote secrecy, universal verifiability, and resistance to double voting under a more efficient cryptographic framework. Our findings contribute to the development of scalable, high-assurance e-voting mechanisms suitable for modern digital infrastructures. The presented modifications significantly enhance the scalability and efficiency of e-voting systems without compromising cryptographic strength.
The purpose of Internet of Things (IoT) security is to ensure the availability, confidentiality, and integrity of IoT networks. However, due to the heterogeneity of IoT devices and the possibility of attacks of various kinds from both inside and outside the network, securing an IoT network is a difficult task. Handshake protocols are useful for achieving mutual authentication, which allows secure inclusion of devices into the network. By verifying that the information they receive is accurate and from a trusted source, mutual authentication minimizes the possibility that a malicious actor will compromise their connections. However, handshake protocols do not protect devices from attackers in the network. Use of autonomous anomaly detection and blacklisting prevents nodes with anomalous behavior from joining, re-joining, or remaining in the network. Similarly, trust scoring is another popular method that can be used to increase the resilience of the network against trust based system attacks. In view of the above, the contributions of this paper are three-fold. First, to ensure the security of the IoT network from outsider attacks in a zero-trust environment, we propose a new handshake protocol based on Physical Unclonable Functions that can be used in IoT device discovery and mutual authentication between the IoT device and the server. The proposed protocol is resilient to Man-in-the-Middle, replay and forgery attacks, as proven in our security analysis. Secondly, we propose a real-time intrusion and anomaly detection framework based on machine learning to prevent network-based attacks from insiders. Finally, we propose a trust system which utilizes feedback mechanisms based on smart contracts for managing the trust of a dynamic IoT network to increase resilience against behavioral attacks. Simulation results show that by using blacklisting, our trust management model provides greater resilience against trust-based attacks compared to similar blockchain-based trust models in the literature, and the proposed distributed IoT network security framework can secure an IoT network from both internal and external attacks, even in an environment where half of the devices in the network are compromised.
Digital payments play a pivotal role in the burgeoning digital economy. Moving forward, the enhancement of digital payment systems necessitates programmability, going beyond just efficiency and convenience, to meet the evolving needs and complexities. Smart contract platforms like Central Bank Digital Currency (CBDC) networks and blockchains support programmable digital payments. However, the prevailing paradigm of programming payment logics involves coding smart contracts with programming languages, leading to high costs and significant security challenges. A novel and versatile method for payment programming on DLTs was presented in this paper - transforming digital currencies into token streams, then pipelining smart contracts to authorize, aggregate, lock, direct, and dispatch these streams efficiently from source to target accounts. By utilizing a small set of configurable templates, a few specialized smart contracts could be generated, and support most of payment logics through configuring and composing them. This approach could substantially reduce the cost of payment programming and enhance security, self-enforcement, adaptability, and controllability, thus hold the potential to become an essential component in the infrastructure of digital economy.
In our research, we propose the first practically deployable construction of a multi-prover zero-knowledge succinct non-interactive argument of knowledge (zkSNARK) protocol specifically tailored for restricted multiplication straight-line (RMS) programs, a computation model widely applicable in evaluating polynomials. Our protocol ensures input privacy, zero-knowledge, and security against fully malicious provers, all while eliminating the need for any inter-prover communication, making it highly suitable for distributed cloud environments. At the core of our approach is the introduction of the Restricted Quadratic Arithmetic Program model, an algebraic structure aligned with RMS semantics that enables provers to independently generate local proofs. We instantiate our framework using the Pinocchio protocol, resulting in a system that requires only 9 group elements per proof and 10 pairings for verification, nearly matching the efficiency of its single-prover counterpart. By leveraging our multi-prover zkSNARK protocol within a multi-server verification computation framework, we enable secure outsourcing of computations to the cloud of fully untrusted cloud servers. Compared to existing works, our protocol uniquely eliminates the need for any inter-server communication while achieving security even against adversaries controlling all servers.
Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda · 9 authors
The rapid adoption of Internet of Medical Things (IoMT) devices enables real-time patient monitoring and remote diagnostics and has revolutionized healthcare delivery. Traditional cryptographic schemes like RSA and ECC, which rely on meaningful mathematical challenges, are under great threat from quantum computing, threatening sensitive medical data confidentiality and integrity. This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). To this end, we design a five-phase IoMT-friendly framework—Initialization, Registration, Authentication, Data Exchange, and Treatment—where each phase is backed up by lightweight cryptography primitives that can be easily implemented on the low-resource IoMT devices. Relative to the state-of-the-art lattice- and hash-based constructions, our framework involves 50-75% smaller ciphertext sizes, up to a 50% reduction of the communication overhead, and nearly 60% less in computational cost. Furthermore, the solution relies on zero-knowledge proofs, homomorphic encryption as well and attribute-based access control to guarantee strong security and privacy. Using the AVISPA tool, the framework is formally verified, showing its resistance against classical and quantum adversaries. Focusing on tangible healthcare threats, including data tampering and unlicensed access to patient diagnostics, this research paves the way for scalable, efficient, and quantum-resistant medical data protection. Our results pave the way for future investigations into secure post-quantum healthcare and IoT applications.
Lambard Maxence, Cyrille Bertelle, D apos Amours Claude
In an increasingly complex contractual landscape, the demand for transparency, security, and efficiency has intensified. Blockchain technology, with its decentralized and immutable nature, addresses these challenges by reducing intermediary costs, minimizing fraud risks, and enhancing system compatibility. Smart contracts, initially conceptualized by Nick Szabo and later implemented on the Ethereum blockchain, automate and secure contractual clauses, offering a robust solution for various industries. However, their complexity and the requirement for advanced programming skills present significant barriers to widespread adoption. This study introduces a multi-level finite state machine model designed to represent and track the execution of smart contracts. Our model aims to simplify smart contract development by providing a formalized framework that abstracts underlying technical complexities, making it accessible to professionals without deep technical expertise. The hierarchical structure of the multi-level finite state machine enhances contract modularity and traceability, facilitating detailed representation and evaluation of functional properties. The paper explores the potential of this multi-level approach, reviewing existing methodologies and tools, and detailing the smart contract generation process with an emphasis on reusable components and modularity. We also conduct a security analysis to evaluate potential vulnerabilities in our model, ensuring the robustness and reliability of the generated smart contracts.
Ensuring secure and efficient authentication in Vehicular Ad Hoc Networks (VANETs) is vital for real-time communication and network resilience. However, traditional authentication mechanisms, such as Elliptic Curve Cryptography (ECC) and Public Key Infrastructure (PKI), face significant challenges, including high computational overhead, complex certificate revocation, and vulnerability to quantum attacks. To overcome these limitations, we propose a lattice-based authentication protocol that integrates post-quantum cryptography (PQC), zero-knowledge proofs (ZKPs), and fog computing for secure Vehicle-to-Roadside (V2R) communication. Our protocol offers quantum resistance, decentralized authentication, and dynamic pseudonym updates, enhancing both security and privacy in VANETs. Performance evaluations demonstrate that our approach achieves lower message delay (0.8), reduced packet loss ratio (0.6), minimal communication overhead (0.7), and the fastest authentication delay (0.5) compared to ECC and Physically Unclonable Function (PUF)-based methods. Additionally, formal security analysis confirms that our scheme effectively mitigates impersonation, replay, tracking, and quantum attacks, ensuring a scalable and future-proof authentication mechanism for next-generation VANETs.
The widespread adoption of e-health systems raises critical concerns regarding data privacy and network security. Ensuring secure and reliable data sharing between patients and healthcare professionals remains a significant challenge. To address this, we propose a novel anonymous authentication scheme tailored for e-health environments, integrating zero-knowledge proof (ZKP) with multimodal biometrics. Our key contributions are as follows: (1) applying the Pedersen vector commitment algorithm to construct a biometric-based ZKP scheme, thereby ensuring enhanced security and privacy-preserving authentication; (2) utilizing multimodal cancelable biometrics generate (MCBG) technology, integrating fingerprint, face, and iris modalities to strengthen the security of the verification process; and (3) providing a detailed security analysis that demonstrates our scheme meets essential security requirements, including anonymity, authenticity, unlinkability, forward security, and resistance to replay attacks. Experimental results demonstrate stable proving and verification time of approximately 78 ms and 140 ms, respectively, regardless of the proof range, validating its efficiency and practicality for secure authentication in e-health systems.